Markers associated with alzheimer&#39;s disease

ABSTRACT

This application discloses SNPs capable of predicting increased or decreased risk of developing late onset Alzheimer&#39;s disease.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit under 35 USC 119(e) of U.S.Provisional Patent Application No. 61/312,855, filed Mar. 11, 2010,which is incorporated herein by reference in its entirety for allpurposes.

FIELD

The present invention relates to genetic markers, compositions for thedetection of genetic markers, and methods for assessing risk ofdeveloping Alzheimer's disease.

BACKGROUND

Disorders of the brain are serious medical conditions causing disabilityand diminished quality of life. Neurological damage is largelyirreversible and thus early diagnosis and close monitoring are criticalto the successful treatment of patients. Alzheimer's disease (AD) is aneurodegenerative disease associated with progressive memory loss andcognitive dysfunction. It is associated with abnormal clumps (amyloidplaques) and tangled bundles of fibers (neurofibrillary tangles) in thebrain, both of which are considered signs of AD. An estimated 4 millionAmericans have AD. By the year 2030 approximately 1 in every 80 personsin the U.S. will have AD. Familial Alzheimer's disease (FAD) is known tobe inherited. In affected families, members of at least two generationshave had the disease. FAD is rare, accounting for less than 1% of allcases of AD. FAD has an earlier onset, i.e., about 40 years of age andcan be observed to run in families.

Early-onset Alzheimer's disease (EOAD) is a rare form of Alzheimer'sdisease in which individuals are diagnosed with the disease before age65. Less than 10% of all Alzheimer's disease patients have EOAD. Youngerindividuals who develop Alzheimer's disease exhibit more of the brainabnormalities that are normally associated with Alzheimer's disease.EOAD is usually familial and follows an autosomal dominant inheritancepattern. To date, mutations in three genes including amyloid precursorprotein (APP) on chromosome 21, presenilin 1 (PSEN1) on chromosome 14and presenilin 2 (PSEN2) on chromosome 1 have been identified infamilies with EOAD. Mutations in the APP, PSEN1 and PSEN2 genes accountfor about 50% of the disease. Most of the pathogenic mutations in theAPP and presenilin genes are associated with abnormal processing of APP,which leads to the overproduction of toxic A˜-1-42. Down syndromepatients, who have three copies of chromosome 21 which includes the APPgene, begin to develop the characteristic senile plaques and tau tanglesat the ages of 30 and 40 (Kamboh, Annals of Human Genetics 68:381-404,2004).

Late-onset Alzheimer's disease (LOAD) is the most common form ofAlzheimer's disease, accounting for about 90% of cases and usuallyoccurring after age 65. LOAD strikes almost half of all individuals overthe age of 85 and may or may not be hereditary. It is a complex andmultifactorial disease with the possible involvement of several genes.Genome-wide linkage or linkage disequilibrium studies on LOAD haveprovided informative data for the existence of multiple putative genesfor AD on several chromosomes, with the strongest evidence onchromosomes 12, 10, 9 and 6. LOAD cases tend to be sporadic, whereinthere is no family history of the disease. Genetic susceptibility atmultiple genes and interaction between these genes as well asenvironmental factors are most likely responsible for the etiology ofLOAD. Twin data on incident cases indicates that almost 80% of the LOADrisk is attributable to genetic factors. The Apolipoprotein E (APOE)gene on chromosome 19q13 has been identified as a strong risk factor forLOAD. In fact, the APOE-ε4 allele has been established as a strongsusceptibility marker that accounts for nearly 30% of the risk inlate-onset AD. More specifically, three variants of APOE, encoded bycodons 112 and 158, have been found to modify the risk of LOAD. Ascompared to the common APOE-ε3 allele (codon 112=Cys and codon 158=Arg),the APOE-ε4 allele (codon 112=Arg and codon 158=Arg) increases the riskof AD, while the APOE-ε2 allele (codon 112=Cys and codon 158=Cys)decreases the risk of AD. The effect of the APOE-ε4 allele is doserelated, wherein one or two copies of the APOE-ε4 allele are associatedwith 3-fold or 15-fold risk, respectively. However, the effect of theAPOE-ε4 allele on AD risk appears to decline with increasing age(Kamboh, 2004, supra).

From the time of diagnosis, people with AD survive about half as long asthose of similar age without dementia. Medicare costs for beneficiarieswith AD were $91 billion in 2005 and may increase to as much as $160billion in 2010. Finding a treatment that could delay the onset by fiveyears could reduce the number of individuals with AD by nearly 50percent after 50 years. Drug development for AD is very active andsensitive diagnostic and screening technologies could identify patientsfor therapy and monitor their response. Improved diagnostic tools for ADwould thus be a significant advancement to drug development for thisdisease and would also provide a way to guide therapeutic decisionmaking thus improving outcomes and reducing unnecessary exposure ofpatients to costly medications with unwanted side effects.

SUMMARY

The present invention relates to genetic markers, compositions for thedetection of genetic markers, and methods for assessing risk ofdeveloping Alzheimer's disease.

In particular, the present invention provides methods of classifying asubject to a late onset Alzheimer's disease risk group, comprising:receiving a sample from the subject; detecting a marker in Table 2; andclassifying the subject into a risk group based upon the presence orabsence of the marker. In some embodiments, the methods furthercomprising isolating nucleic acid from the sample. In some embodiments,the marker is detected directly. In some of these embodiments, themarker detection comprises a method selected from the group consistingof Sanger sequencing, pyrosequencing, SOLID sequencing, massivelyparallel sequencing, barcoded DNA sequencing, PCR, real-time PCR,quantitative PCR, microarray analysis of genomic DNA with a gene chip,restriction fragment length polymorphism analysis, allele specificligation, and comparative genomic hybridization. In other embodiments,the marker is detected indirectly. In some of these embodiments, themarker detection comprises a method selected from the group consistingof microarray analysis of RNA, RNA in situ hybridization, RNAseprotection assay, Northern blot, reverse transcriptase PCR, quantitativePCR, quantitative reverse transcriptase PCR, quantitative real-timereverse transcriptase PCR, reverse transcriptase treatment followed bydirect sequencing, flow cytometry, immunohistochemistry, ELISA, Westernblot, immunoaffinity chromatograpy, HPLC, mass spectrometry, proteinmicroarray analysis, PAGE analysis, isoelectric focusing, and 2-D gelelectrophoresis. In some embodiments, the marker is associated with ahigh risk of developing LOAD and the subject is classified to a riskgroup with high risk of LOAD if the marker is detected in the sample. Ina subset of these embodiments, the subject is further classified basedon the presence or absence of the APOE-ε4 allele. In some embodiments,the marker is associated with a low risk of developing LOAD and thesubject is classified to a risk group with low risk of LOAD if themarker is detected in the sample. In a subset of these embodiments, themarker is the A allele of rs17042395. In some embodiments, the subjectis further classified based on the presence of two copies of the APOE-e3allele.

In addition, the present invention provides sets of molecular probesused in assessing the risk of developing late onset Alzheimer's disease(LOAD) comprising: a first probe capable of detecting a first SNPselected from Table 2; and a second probe capable of detecting a secondSNP selected from Table 2; wherein the probes are associated with amicroarray of 1000 or fewer elements. In some embodiments, the firstprobe is capable of detecting a SNP associated with a higher risk ofdeveloping LOAD. In some embodiments, the second probe is capable ofdetecting a SNP associated with a lower risk of developing AD. In otherembodiments, the first probe and the second probe are capable ofdetecting a SNP associated with a lower risk of developing LOAD. In somepreferred embodiments, the first probe detects the A allele ofrs17042395 and the second probe detects the apoe3 allele.

Moreover, the present invention provides methods of classifying asubject to a late onset Alzheimer's disease (LOAD) risk group,comprising: receiving a sample from the subject; detecting an A alleleof rs17042395; detecting an E3 allele of APOE; and classifying thesubject in a low LOAD risk group if both the A allele of rs17042395 andthe E3 allele of APOE are detected. In some embodiments, the methodsfurther comprise isolating nucleic acid from the sample. In someembodiments, the marker is detected directly. In some of theseembodiments, the marker detection comprises a method selected from thegroup consisting of Sanger sequencing, pyrosequencing, SOLID sequencing,massively parallel sequencing, barcoded DNA sequencing, PCR, real-timePCR, quantitative PCR, microarray analysis of genomic DNA with a genechip, restriction fragment length polymorphism analysis, allele specificligation, and comparative genomic hybridization. In some embodiments,the marker is detected indirectly. In some of these embodiments, themarker detection comprises a method selected from the group consistingof microarray analysis of RNA, RNA in situ hybridization, RNAseprotection assay, Northern blot, reverse transcriptase PCR, quantitativePCR, quantitative reverse transcriptase PCR, quantitative real-timereverse transcriptase PCR, reverse transcriptase treatment followed bydirect sequencing, flow cytometry, immunohistochemistry, ELISA, Westernblot, immunoaffinity chromatograpy, HPLC, mass spectrometry, proteinmicroarray analysis, PAGE analysis, isoelectric focusing, and 2-D gelelectrophoresis.

DETAILED DESCRIPTION

In the following description, and for the purposes of explanation,numerous specific details are set forth in order to provide a thoroughunderstanding of the various aspects of the invention. It will beunderstood, however, by those skilled in the relevant arts, that thepresent invention may be practiced without these specific details. Inother instances, known structures and devices are shown or discussedmore generally in order to avoid obscuring the invention.

Aspects and applications of the invention presented here are describedbelow in the drawings and detailed description of the invention. Unlessspecifically noted, it is intended that the words and phrases in thespecification and the claims be given their plain, ordinary, andaccustomed meaning to those of ordinary skill in the applicable arts.

If a noun, term, or phrase is intended to be further characterized,specified, or narrowed in some way, then such noun, term, or phrase willexpressly include additional adjectives, descriptive terms, or othermodifiers in accordance with the normal precepts of English grammar.Absent the use of such adjectives, descriptive terms, or modifiers, itis the intent that the noun, term, or phrase is given its broadestpossible meaning.

The use of the words “function,” “means” or “step” herein is notintended to somehow indicate a desire to invoke the special provisionsof 35 U.S.C. §112, ¶6, to define the invention. To the contrary, if theprovisions of 35 U.S.C. §112, ¶6 are sought to be invoked to define theinventions, the claims will specifically and expressly state the exactphrases “means for” or “step for, and will also recite the word“function” (i.e., will state “means for performing the function of[insert function]”), without also reciting in such phrases anystructure, material or act in support of the function. Thus, even whenthe claims recite a “means for performing the function of . . . ” or“step for performing the function of . . . ,” if the claims also reciteany structure, material or acts in support of that means or step, orthat perform the recited function, then the provisions of 35 U.S.C.§112, ¶6 are not invoked. Moreover, even if the provisions of 35 U.S.C.§112, ¶6 are invoked to define the claimed inventions, it is intendedthat the inventions not be limited only to the specific structure,material or acts that are described in the preferred embodiments, but inaddition, include any and all structures, materials or acts that performthe claimed function as described in alternative embodiments or forms ofthe invention, or that are well known present or later-developed,equivalent structures, material or acts for performing the claimedfunction.

Alzheimer's disease (AD) is a progressive neurodegenerative disordercharacterized by memory and cognitive impairments and othernon-cognitive behavioral symptoms. Age is the strongest risk factor,wherein almost 50% of people over the age of 85 are affected. Earlyonset AD (EOAD) is associated with genetic mutations in amyloidprecursor protein (APP), presenilin I (PSENI) and presenilin 2 (PSEN2).However, sporadic or late-onset AD (LOAD) is multi-factorial andgenetically more complex. In addition, genetic factors may account foras much as 80% of the disease risk associated with LOAD (Gatz et al.(2006) Arch. Gen. Psychiatry 63(2):168-174). While monogenic mutationscause EOAD, the only extensively validated susceptibility gene for LOADis the apolipoprotein E (APOE-e4) allele (Saunders et al. (1993)Neurology 43(8):1467-1472 and Farrer et al. (1997) JAMA 278(16):1349-1356). But alleles of the APOE gene do not account for all of thegenetic load responsible for LOAD predisposition. Stratification byAPOE-ε4 carrier status allows for the detection of association signalsthat are normally overwhelmed and thus, masked by the signal of APOEalleles in a non-stratified study design.

AD is the most common cause of disabling memory and thinking problems inolder persons. According to one study, it afflicts about 10% of thoseover the age of 65 and almost half of those over the age of 85.According to another study, the prevalence of the disorder increasesfrom I% by the age of 60 years to 40% in nonagenarians (See Reference1). By 2050, the number of afflicted persons is projected to quadruple,leading to ˜16 million patients and a cost of more than $750 billion peryear (with no adjustment for inflation) in the United States alone.Meantime, the disorder takes a devastating toll on patients and theirfamilies. Clinically, AD is characterized by gradual but progressivedeclines in memory, language skills, ability to recognize objects orfamiliar faces, ability to perform routine tasks, and judgment andreasoning. Associated features commonly include agitation, paranoiddelusions, sleepiness, aggressive behaviors, and wandering. In its mostsevere form, patients may be confused, bed-ridden, unable to controltheir bladder or bowel functions, or swallow. By contributing to otherproblems (e.g., inanition and infections), it is considered the fourthleading cause of death in the United States. Neuropathologically, AD ischaracterized by the accumulation of neuritic plaques (the majorcomponent of which is the amyloid-B peptide [Aβ], neurofibrillarytangles (NFT, the major component of which is the hyper-phosphorylatedform of the protein tau). While the etiology leading to the developmentof AD has not been clearly resolved, genetic factors play a major role.

Twin studies report a higher concordance of AD among monozygoticcompared to dizygotic twins, with heritability estimates between 60% and80% (See Reference 2). Some rare forms of the disease (<1% by someestimates) are caused by more than 200 mutations in the genes encodingthe amyloid precursor protein (APP), presenilin I (PSI) and presenilin 2(PS2). These mutations, which influence directly the production of Aβ,cause a form of AD characterized by autosomal dominant inheritance andan early age of dementia onset (typically before the age of 60).However, the majority of AD cases are not dominantly inherited and thereis a broad consensus that AD is genetically complex and heterogeneousand that genetic polymorphisms contribute substantially to the risk ofdisease.

The ε4 allele of the apolipoprotein E (APOE) genotype is the onlywell-established genetic susceptibility factor for sporadic or familialAD (See Reference 4). While subsequent association studies havesuggested the existence of additional AD susceptibility genes, most ofthe results have not been replicated consistently. A variety ofapproaches, each with its strengths and limitations, are being taken inan attempt to discover additional AD susceptibility genes. One approachis the use of genome-wide scans.

Large case-control association studies are one approach being toidentify genes that predispose to genetically complex neuropsychiatricdisorders (See Reference 8). In AD, the candidate-gene approach has beenmostly used in case-control association studies because it isstraightforward and because it uses information generated in previousepidemiologic studies or laboratory experiments. The development ofdense, genome-wide genotyping technologies such as the 100 k and 500 kSNP genotyping chips by Affymetrix allowed, for the first time, ahypothesis-free approach in the genetics of such complex diseases as AD.Reiman et al. previously applied this approach to a set of 1,411 samplesthat included 1,044 post-mortem neuropathologically verified cases andcontrols. After multiple testing corrections, the only locus thatremained significant in the whole genome screen was APOE (See Reference9).

Based on the hypothesis that the signal from APOE could be overwhelmingother significantly associated loci, the cohort was stratified intothose who were carriers of the APOE-ε4 risk allele and those who werenon-carriers and the analysis was repeated in these subgroups. Amongthose who were carriers of APOE-ε4, a significant association wasdetected between AD and the Grb-2 associated binding protein (GAB2) (SeeReference 10). Set association analysis also produced a set of 5 SNPsthat improved genetic risk assessment of late onset AD, particularly forthose who were not carriers of the APOE-ε4 risk allele.

In people with AD, changes in the brain may begin 10 to 20 years beforeany visible signs or symptoms appear. Some regions of the brain maybegin to shrink, resulting in memory loss, the first visible sign of AD.Over time, AD progresses through three main stages: mild, moderate, andsevere. These stages are characterized by a collection of signs andsymptoms and behaviors that individuals with AD experience. People withmild symptoms of AD often seem healthy, but they are actually havingdifficulty making sense of the world around them. Initial symptoms areoften confused with changes that take place in normal aging. Symptomsand early signs of AD may include difficulty learning and rememberingnew information, difficulty managing finances, planning meals, takingmedication on schedule, depression symptoms (sadness, decreased interestin usual activities, loss of energy), getting lost in familiar places,etc. In moderate AD, the damaging processes occurring in the brainworsen and spread to other areas that control language, reasoning,sensory processing, and thought. In this stage, symptoms and signs of ADbecome more pronounced and behavioral problems may become more obvious.Signs and symptoms of moderate AD may include forgetting old facts,repeating stories and/or questions over and over, making up stories tofill gaps, difficulty performing tasks, following written notes,agitation, restlessness, repetitive movements, wandering, paranoia,delusions, hallucinations, deficits in intellect and reasoning, lack ofconcern for appearance, hygiene, and sleep, etc. In the advanced stageof AD, damage to the brain's nerve cells is widespread. At this point,full-time care is typically required. People with severe AD may havedifficulty walking, and they often suffer complications from otherillnesses, such as pneumonia. Signs of severe AD may include screaming,mumbling, speaking gibberish, refusing to eat, failing to recognizefamily or faces, and difficulty with all essential activities of dailyliving.

A single polynucleotide polymorphism (or SNP) may be any DNA sequencevariation that involves a change in a single nucleotide.

A haplotype may be any combination of one or more closely linked allelesinherited as a unit. Different combinations of polymorphisms may also becalled haplotypes. The difference of a single genetic marker candelineate a distinct haplotype. Alternatively, the results from severalloci could be referred to as a haplotype. For example, a haplotype canbe a set of SNPs on a single chromatid that are statistically associatedto be likely to be inherited as a unit. Two or more alleles likely to beinherited as a unit may be termed a haplotype block. The haplotype blockmay, in turn, be used to identify other polymorphic sites in its region.Upon identification of a haplotype block associated with a particularhaplotype, one of skill in the art may readily identify all other DNApolymorphisms associated with the particular haplotype by routinesequencing of the genomic DNA of an individual having such haplotype(such as an individual homozygous for such haplotype).

An allele includes any form of a particular nucleic acid that may berecognized as a form of the particular nucleic acid on account of itslocation, sequence, or any other characteristic. Alleles include butneed not be limited to forms of a gene that include point mutations,silent mutations, deletions, frameshift mutations, single nucleotidepolymorphisms (SNPs), inversions, translocations, heterochromaticinsertions, and differentially methylated sequences relative to areference gene, whether alone or in combination. The presence or absenceof an allele may be detected through the use of any process throughwhich a specific nucleic acid molecule may be detected, including directand indirect methods of detecting the presence or absence of an allele.An allele may occur in a non-coding or coding region of a genome. If itis in a coding region, it may affect a particular triplet codon. If theallele does affect the codon, it may change the amino acid in theprotein resulting from expression of the allele. An exception is if theallele is a silent mutation. In that case, the allele is a mutation inthe coding region that does not change the amino acid that the codonencodes. An allele may also be called a mutation or a mutant. An allelemay be compared to another allele that may be termed a wild type form ofan allele. In some cases, the wild type allele is more common than themutant.

When a SNP haplotype block is identified by a SEQ ID NO, a set of atleast two SNPs that are associated with an allele of a gene are groupedtogether in the form of a synthetic nucleotide sequence. Detecting theSNPs in a given haplotype block in a subject may be associated with agreater or lesser risk that the subject will develop LOAD. A nucleicacid may be termed to be specific to a SNP haplotype block or specificto a SNP within a haplotype block. A nucleic acid specific to ahaplotype block or a SNP within a haplotype block contains sequence thatis complementary to at least one SNP that is grouped within thathaplotype block. Such nucleic acids may be complementary to a SNP thatis associated with the synthetic nucleotide sequence or any other SNPassociated within the haplotype identified by the SNP haplotype block.

The HapMap is a catalog of common genetic variants that occur in humanbeings. It describes what these variants are, where they occur in theDNA, and how they are distributed among individuals within populationsand among populations in different parts of the world (See the followingreference: A haplotype map of the human genome (2005) Nature437:1299-1320).

A marker may be any molecular structure produced by a cell, expressedinside the cell, accessible on the cell surface, or secreted by thecell. A marker may be any protein, carbohydrate, fat, nucleic acid,catalytic site, or any combination of these such as an enzyme,glycoprotein, cell membrane, virus, cell, organ, organelle, or any uni-or multimolecular structure or any other such structure now known or yetto be disclosed whether alone or in combination. A marker may also becalled a target and the terms are used interchangeably.

A marker may be represented by the sequence of a nucleic acid from whichit can be derived or any other chemical structure. Examples of suchnucleic acids include miRNA, tRNA, siRNA, mRNA, cDNA, or genomic DNAsequences including complimentary sequences. Alternatively, a marker maybe represented by a protein sequence. The concept of a marker is notlimited to the products of the exact nucleic acid sequence or proteinsequence by which it may be represented. Rather, a marker encompassesall molecules that may be detected by a method of assessing theexpression of the marker.

Examples of molecules encompassed by a marker represented by aparticular sequence or structure include point mutations, silentmutations, deletions, frameshift mutations, translocations, alternativesplicing derivatives, differentially methylated sequences,differentially modified protein sequences, truncations, soluble forms ofcell membrane associated markers, and any other variation that resultsin a product that may be identified as the marker. The followingnonlimiting examples are included for the purposes of clarifying thisconcept: If expression of a specific marker in a sample is assessed byRTPCR, and if the sample expresses an mRNA sequence different from thesequence used to identify the specific marker by one or morenucleotides, but the marker may still be detected using RTPCR, then thespecific marker encompasses the sequence present in the sample.Alternatively if expression of a specific marker in a sample is assessedby an antibody and the amino acid sequence of the marker in the samplediffers from a sequence used to identify marker by one or more aminoacids, but the antibody is still able to bind to the version of themarker in the sample, then the specific marker encompasses the sequencepresent in the sample.

The genetic sequences of different individuals are remarkably similar.When the chromosomes of two humans are compared, their DNA sequences canbe identical for hundreds of bases. But at about one in every 1000 to1,200 bases, on average, the sequences will differ. As such, oneindividual might have an A at that location, while another individualhas a G, or a person might have extra bases at a given location or amissing segment of DNA. Differences in individual bases are the mostcommon type of genetic variation. These genetic differences are known assingle nucleotide polymorphisms (SNPs) (supra). SNPs act as markers tolocate genes in DNA. Given the relatively close spacing between theseSNPs, SNPs are typically inherited in blocks.

The invention provides a method of assigning a subject to a late onsetAlzheimer's disease (LOAD) risk group in order to assess the likelihoodof the subject being afflicted with the disease. This method can beemployed to assess the risk at early stages of disease progression. Themethod includes providing a biological sample from the subject,detecting a marker in a biological sample, which can be a haplotypeassociated with LOAD and assigning the subject to the late onsetAlzheimer's disease (LOAD) risk group based upon the presence or absenceof the haplotype. The method involves directly or indirectly detectingthe presence or absence of the markers. In addition, the subject may befurther stratified by LOAD risk group based upon whether the subjectcarries an apolipoprotein E allele associated with increased or alteredLOAD risk. By way of example, APOE-ε4 is commonly associated with LOAD.In addition, various haplotypes of APOE have been associated with LOADrisk groups as set forth in U.S. Patent Publ. 2005/0277129. Finallymultiple markers disclosed herein may be used in combination to improvethe accuracy, preferably two or more, three or more, four or more, fiveor more, or ten or more of the markers may be used.

The invention contemplates that markers may be detected by a variety ofmethodologies or procedures that are well know in the art including, butnot limited to, nucleic acid hybridization, antibody binding, activityassay, polymerase chain reaction (PCR), SI nuclease assay and via genechip or microarray as well as any other assay known in the art that maybe used to detect the SNPs associated with a haplotype or the geneproduct produced from the gene of the haplotype including mRNA andprotein. Hybridization of a SNP-specific oligonucleotide to a targetpolynucleotide may be performed with both entities in solution, or suchhybridization may be performed when either the oligonucleotide or thetarget polynucleotide is covalently or noncovalently affixed to a solidsupport. Attachment may be mediated, for example, by antibody-antigeninteractions, poly-L-Lys, streptavidin or avidin-biotin interactions,salt bridges, hydrophobic interactions, chemical linkages, UVcross-linking baking, etc. SNP-specific oligonucleotides may besynthesized directly on the solid support or attached to the solidsupport subsequent to synthesis. Solid-supports suitable for use indetection methods of the invention include substrates made of silicon,glass, plastic, paper and the like, which may be formed, for example,into wells (as in 96-well plates), slides, sheets, membranes, fibers,chips, dishes, and beads. The solid support may be treated, coated orderivatized to facilitate the immobilization of the SNP-specificoligonucleotide or target nucleic acid. Detecting the nucleotide ornucleotide pair of interest may also be determined using a mismatchdetection technique, including but not limited to the RNase protectionmethod using riboprobes (Winter et al. (1985) Proc. Natl. Acad. Sci. USA82:7575; Meyers et al. (1985) Science 230:1242) and proteins whichrecognize nucleotide mismatches, such as the E. coli mutS protein(Modrich (1991) Ann. Rev. Genet. 25:229-53). Alternatively, variant SNPsor variant alleles can be identified by single strand conformationpolymorphism (SSCP) analysis (Orita et at. (1989) Genomics 5:874-9);Humphries et al. (1996) in MOLECULAR DIAGNOSIS OF GENETIC DISEASES,Elles, ed., pp. 321-340) or denaturing gradient gel electrophoresis(DGGE) (Wartell et al. (1990) Nucl. Acids Res. 18:2699706); Sheffield etal. (1989) Proc. Natl. Acad. Sci. USA 86:232-6). A polymerase-mediatedprimer extension method may also be used to identify thepolymorphism(s). Several such methods have been described in the patentand scientific literature and include the “Genetic Bit Analysis” method(WO 92/15712) and the ligase/polymerase mediated genetic bit analysis(U.S. Pat. No. 5,679,524. Related methods are disclosed in WO 91102087,WO 90/09455, WO 95/17676, and U.S. Pat. Nos. 5,302,509 and 5,945,283.Extended primers containing the complement of the polymorphism may bedetected by mass spectrometry as described in U.S. Pat. No. 5,605,798.Another primer extension method is allele-specific PCR (Ruano et al.(1989) Nucl. Acids Res. 17:8392; Ruano et al. (1991) Nucl. Acids Res.19:6877-82); WO 93/22456; Turki et al. (1995) 1. Clin. Invest.95:1635-41). The haplotype for a gene of an individual may also bedetermined by hybridization of a nucleic acid sample containing one orboth copies of the gene, mRNA, cDNA or fragment(s) thereof, to nucleicacid arrays and sub-arrays such as described in WO 95/112995. The arrayswould contain a battery of SNP-specific or allele specificoligonucleotides representing each of the polymorphic sites to beincluded in the haplotype.

Detecting the presence or absence of a marker disclosed herein or aclose isoform thereof may be carried out either directly or indirectlyby any suitable methodology. A variety of techniques are known to thoseskilled in the art (supra). All generally involve receiving a biologicalsample containing DNA or protein from the subject, and then detectingwhether or not the marker or a close isoform thereof is present in thesample. and then determining the presence or absence of the marker inthe sample.

The sample may be any type of sample derived from the subject, includingany fluid or tissue that may contain one or more markers associated withthe haplotype. Examples of sources of samples include but are notlimited to biopsy or other in vivo or ex vivo analysis of prostate,breast, skin, muscle, fascia, brain, endometrium, lung, head and neck,pancreas, small intestine, blood, liver, testes, ovaries, colon, skin,stomach, esophagus, spleen, lymph node, bone marrow, kidney, placenta,or fetus. In some aspects of the invention, the sample comprises a fluidsample, such as peripheral blood, lymph fluid, ascites, serous fluid,pleural effusion, sputum, cerebrospinal fluid, amniotic fluid, lacrimalfluid, stool, or urine.

The marker may be detected by any of a number of methods. Direct methodsof detecting the presence of an allele include but are not limited toany form of DNA sequencing including Sanger, next generation sequencing,pyrosequencing, SOLID sequencing, massively parallel sequencing, pooled,and barcoded DNA sequencing or any other sequencing method now known oryet to be disclosed; PCR-based methods such as real-time PCR,quantitative PCR, reverse transcription PCR or any combination of these;allele specific ligation; comparative genomic hybridization; or anyother method that allows the detection of a particular nucleic acidsequence within a sample or enables the differentiation of one nucleicacid from another nucleic acid that differs from the first nucleic acidby one or more nucleotides. A sample may be from a subject suspected ofhaving AD. Nucleic acids may include but need not be limited to RNA,cDNA, tRNA, mitochondrial DNA, plasmid DNA, siRNA, genomic DNA, or anyother naturally occurring or artificial nucleic acid molecule. A subjectmay be any organism that may be subject to degenerative neurologicaldiseases including mammals, further including humans.

In Sanger Sequencing, a single-stranded DNA template, a primer, a DNApolymerase, \nucleotides and a label such as a radioactive labelconjugated with the nucleotide base or a fluorescent label conjugated tothe primer, and one chain terminator base comprising a dideoxynucleotide(ddATP, ddGTP, ddCTP, or ddTTP, are added to each of four reaction (onereaction for each of the chain terminator bases). The sequence may bedetermined by electrophoresis of the resulting strands. In dyeterminator sequencing, each of the chain termination bases is labeledwith a fluorescent label of a different wavelength which allows thesequencing to be performed in a single reaction.

In pyrosequencing, the addition of a base to a single stranded templateto be sequenced by a polymerase results in the release of aphyrophosphate upon nucleotide incorporation. An ATP sulfyrlase enaymeconverts pyrophosphate into ATP which in turn catalyzes the conversionof luciferin to oxyluciferin which results in the generation of visiblelight that is then detected by a camera.

In SOLID sequencing, the molecule to be sequenced is fragmented and usedto prepare a population of clonal magnetic beads (in which each bead isconjugated to a plurality of copies of a single fragment) with anadaptor sequence and alternatively a barcode sequence. The beads arebound to a glass surface. Sequencing is then performed through 2-baseencoding.

In massively parallel sequencing, randomly fragmented targeted DNA isattached to a surface. The fragments are extended and bridge amplifiedto create a flow cell with clusters, each with a plurality of copies ofa single fragment sequence. The templates are sequenced by synthesizingthe fragments in parallel. Bases are indicated by the release of afluorescent dye correlating to the addition of the particular base tothe fragment.

Examples of indirect methods of detection include any nucleic aciddetection method including the following nonlimiting examples,microarray analysis, RNA in situ hybridization, RNAse protection assay,Northern blot, reverse transcriptase PCR, quantitative PCR, quantitativereverse transcriptase PCR, quantitative real-time reverse transcriptasePCR, reverse transcriptase treatment followed by direct sequencing,direct sequencing of genomic DNA, or any other method of detecting aspecific nucleic acid now known or yet to be disclosed. Other examplesinclude any process of assessing protein expression including flowcytometry, immunohistochemistry, ELISA, Western blot, and immunoaffinitychromatograpy, HPLC, mass spectrometry, protein microarray analysis,PAGE analysis, isoelectric focusing, 2-D gel electrophoresis, or anyenzymatic assay.

Other methods used to assess expression include the use of natural orartificial ligands capable of specifically binding a marker. Suchligands include antibodies, antibody complexes, conjugates, naturalligands, small molecules, nanoparticles, or any other molecular entitycapable of specific binding to a marker. Antibodies may be monoclonal,polyclonal, or any antibody fragment including an Fab, F(ab)₂, Fv, scFv,phage display antibody, peptibody, multispecific ligand, or any otherreagent with specific binding to a marker. Ligands may be associatedwith a label such as a radioactive isotope or chelate thereof, dye(fluorescent or nonfluorescent) stain, enzyme, metal, or any othersubstance capable of aiding a machine or a human eye fromdifferentiating a cell expressing a marker from a cell not expressing amarker. Additionally, expression may be assessed by monomeric ormultimeric ligands associated with substances capable of killing thecell. Such substances include protein or small molecule toxins,cytokines, pro-apoptotic substances, pore forming substances,radioactive isotopes, or any other substance capable of killing a cell.

Other markers may also be used that are associated with the markersdisclosed herein such as SNPs or other polymorphic markers that are inclose enough proximity to have a statistically significant associationwith the marker disclosed herein (i.e., other markers in linkagedisequilibrium with a marker disclosed herein). For example, if a markeror a close isoform thereof is detected in the subject, then the subjectmay be placed into a group either at higher or lower risk for LOADdepending on which marker or close isoform thereof is identified (i.e.,a significant enough number of markers associated with a haplotype).

The invention also provides set of molecular probes for detection,including at least two probes capable of detecting, directly orindirectly, a marker disclosed herein associated with increased ordecreased risk of LOAD, wherein the molecular probes are not associatedwith a microarray of greater than 1000 elements, a microarray withgreater than 500 elements, a microarray with greater than 100 elements,a microarray with greater than 50 elements, or are not associated with amicroarray. Such sets of two or more probes may include at least oneprobe capable of detecting, directly or indirectly, a marker disclosedherein associated with higher risk of developing LOAD and at least oneother probe is capable of detecting, directly or indirectly, a markerdisclosed herein associated with lower risk of developing LOAD.

The expression of the marker in a sample may be compared to a level ofexpression predetermined to predict the presence or absence of aparticular physiological characteristic. The level of expression may bederived from a single control or a set of controls. A control may be anysample with a previously determined level of expression. A control maycomprise material within the sample or material from sources other thanthe sample. Alternatively, the expression of a marker in a sample may becompared to a control that has a level of expression predetermined tosignal or not signal a cellular or physiological characteristic. Thislevel of expression may be derived from a single source of materialincluding the sample itself or from a set of sources. Comparison of theexpression of the marker in the sample to a particular level ofexpression results in a prediction that the sample exhibits or does notexhibit the cellular or physiological characteristic.

Prediction of a cellular or physiological characteristic includes theprediction of any cellular or physiological state that may be predictedby assessing the expression of a marker. Examples include the identityof a cell as a particular cell including a particular normal or diseasedcell type, the likelihood that one or more diseases is present orabsent, the likelihood that a present disease will progress, remainunchanged, or regress, the likelihood that a disease will respond or notrespond to a particular therapy, or any other disease outcome. Furtherexamples include the likelihood that a cell will move, senesce,apoptose, differentiate, metastasize, or change from any state to anyother state or maintain its current state.

One type of cellular or physiological characteristic is the risk that aparticular disease outcome will occur. Assessing this risk includes theperforming of any type of test, assay, examination, result, readout, orinterpretation that correlates with an increased or decreasedprobability that an individual has had, currently has, or will develop aparticular disease, disorder, symptom, syndrome, or any conditionrelated to health or bodily state. Examples of disease outcomes include,but need not be limited to survival, death, progression of existingdisease, remission of existing disease, initiation of onset of a diseasein an otherwise disease-free subject, or the continued lack of diseasein a subject in which there has been a remission of disease. Assessingthe risk of a particular disease encompasses diagnosis in which the typeof disease afflicting a subject is determined. Assessing the risk of adisease outcome also encompasses the concept of prognosis. A prognosismay be any assessment of the risk of disease outcome in an individual inwhich a particular disease has been diagnosed. Assessing the riskfurther encompasses prediction of therapeutic response in which atreatment regimen is chosen based on the assessment. Assessing the riskalso encompasses a prediction of overall survival after diagnosis.

Determining whether or not the presence of an allele signifies aphysiological or cellular characteristic may be assessed by any of anumber of methods. The skilled artisan will understand that numerousmethods may be used to select a marker or a plurality of markers thatsignifies a particular physiological or cellular characteristic. Indiagnosing the presence of a disease, a threshold value may be obtainedby performing the assay method on samples obtained from a population ofpatients having a certain type of disease (Alzheimer's disease forexample,) and from a second population of subjects that do not have thedisease. In assessing disease outcome or the effect of treatment, apopulation of patients, all of which may develop a disease such as AD,may be followed for a period of time. After the period of time expires,the population may be divided into two or more groups. For example, thepopulation may be divided into a first group of patients who did developAD and a second group of patients who did not develop AD. Examples ofendpoints include occurrence of one or more symptoms of disease, death,formation of neurofibrillary tangles, memory loss, or other states towhich the given disease may progress. If presence of the marker in asample statistically aligns with one group relative to the other group,the subject from which the sample was derived may be assigned a risk ofhaving the same outcome as the patient group that differentiallydisplays the marker.

Other methods may be used to assess how accurately the presence orabsence of a marker signifies a particular physiological or cellularcharacteristic. Such methods include a positive likelihood ratio,negative likelihood ratio, odds ratio, and/or hazard ratio. In the caseof a likelihood ratio, the likelihood that the presence or absence ofthe marker would be found in a sample with a particular cellular orphysiological characteristic is compared with the likelihood that thepresence or absence of the marker would be found in a sample lacking theparticular cellular or physiological characteristic.

An odds ratio measures effect size and describes the amount ofassociation or non-independence between two groups. An odds ratio is theratio of the odds of a marker being present or absent in one set ofsamples versus the odds of the marker being present or absent in theother set of samples. An odds ratio of 1 indicates that the event orcondition is equally likely to occur in both groups. An odds ratiograter or less than 1 indicates that presence or absence of the markeris more likely to occur in one group or the other depending on how theodds ratio calculation was set up.

A hazard ratio may be calculated by estimate of relative risk. Relativerisk is the chance that a particular event will take place. It is aratio of the probability that an event such as development orprogression of a disease will occur in samples in which a particularmarker is present over the probability that the event will occur insamples in which the particular marker is absent. Alternatively, ahazard ratio may be calculated by the limit of the number of events perunit time divided by the number at risk as the time interval decreases.In the case of a hazard ratio, a value of 1 indicates that the relativerisk is equal in both the first and second groups; a value greater orless than 1 indicates that the risk is greater in one group or another,depending on the inputs into the calculation.

Detection of the disease also includes detection of the haplotype by anySNPs/markers within the haplotype, but also indirectly throughSNPs/markers outside the haplotype and leveraging linkage disequilibriumto identify carriers of the haplotype. In addition to determining apatient's relative risk for LOAD, the diagnosis may include prescribingtherapeutic regimens to treat, prevent or delay onset of LOAD.

The method of diagnosis will further include direct or indirectdetection of APOE alleles associated with LOAD, preferably the APOE-ε4allele. Such detection may be performed using any of the detectionmethods available to one of skill in the art and the markers disclosedherein and APOE alleles may be detected using the same or differentmethods and may be detected at the same or different times. Further, themethod of diagnosis may rely upon the information regarding the APOEalleles of the subject that had been previously determined. Withinformation regarding any marker disclosed herein and APOE alleles of asubject, the diagnosis of risk may be determined and present in the formof Odds Ratio (OR) or other estimates for the set of alleles possessedby the subject.

EXAMPLES

Elements and acts in the example are intended to illustrate theinvention for the sake of simplicity and have not necessarily beenrendered according to any particular sequence or embodiment.

Example 1 Identification of SNPs Associated with LOAD

Only 46% of haplotypic variation from the CEPH population of the humanHapMap may be captured by the Affymetrix 500K Mapping Assay. As aresult, discoverable odds ratios in this study ranged from 2.0 to as lowas 1.1-1.3. Use of discoverable odds ratios in this range require astudy with greater statistical power, and in turn larger sample sizes.As a result, a genome-wide association study was performed that uses theAffymetrix 6.0 Array which measures ˜906,000 SNPs (representing 85-95%genomic coverage) and ˜946,000 copy number variations (CNVs), with adiscovery cohort of over 2900 samples.

Generally, this type of study presents challenges due to biologic andphenotypic heterogeneity. The pathology of AD may present as a dementiasyndrome, as MCI, or be present in persons without cognitive impairment.Additionally, Alzheimer's dementia is frequently due to a combination ofAD pathology in addition to other common age-related pathlogies (e.g.,cerebral infarctions). A typical approach to this problem is to createlarge sample sizes in order to detect a small signal from backgroundheterogeneity. Along with the large sample size, this study usedneuropathologically verified cases and controls to further controlheterogeneity. This study also used quantitative endophenotypes thatcapture the range of clinical status (e.g., level of and change incognitive function) and the spectrum of neuropathology (e.g.,quantitative measures of AD pathology). Thus, two of the additionalcohorts used herein are longitudinal, epidemiologic clinical pathologicstudies that include a wide range of quantitative data.

All samples were genotyped on the Affymetrix platform. Of those samples400 were selected for genotyping on the Illumina platform. The selectionof the 400 samples was based on the availability of whole genomeexpression data for these samples. Overall, the study performedgenotyping analysis on about 2,600 subjects.

The samples were of three types: clinically diagnosed andneuropathologically confirmed LOAD cases and controls (approximately2025 samples), neuropathologically characterized samples from alongitudinal epidemiological cohort (approximately 700 samples, some ofwhich qualify as LOAD cases and controls), and antemortem samples fromthe Banner PET cohort from individuals genetically likely to develop AD(approximately 200 samples). The Rush cohort and PET cohort were used astwo endophenotype replication cohorts.

The genotype results from each individual were imputed to increase thegenome coverage and also to “clean” the data by re-calling each SNPaccording to the LD structure and genotype calls of the neighboringSNPs. Extending the SNP set from 1 million to 2.4 million SNPs alsoallowed for identification of loci with multiple significant SNPs ratherthan a single significant SNP.

Structure and principle components analysis was used to assess theextent of stratification and admixture in a set of 1,000 unlinked SNPsin each individual. The discovery set includes approximately 2025 LOADcases (Braak and Braak score V or VI, Cerad B or C, clinical diagnosisof possible or probable Alzheimer's disease) and controls (Braak andBraak score I or II, Cerad 0 or A, no clinical diagnosis of dementia)from several independent cohorts. Power estimates for the discoverycohort are listed below:

TABLE 1 Power to detect effects in the discovery cohort (alpha = 0.001,two-sided test, D > 0.7) Disease Allele Allellic Odds Ratio Frequency1.3 1.2 1.1 40% 100% 77% 22% 30% 99% 70% 18% 20% 97% 54% 12% 10% 77% 25%5% 5% 37% 9% 2% 1% 9% 2% 1%Analyses were performed through the use of the following strategies:

A. Single SNP Permutation Analyses

As the number of SNPs increases with denser platforms and imputation,the multiple testing considerations increase, particularly since imputeddata sets contain up to 2.4 million SNPs Therefore, maxT permutationanalyses was used to control for multiple tests rather than a Bonferronior Sidak correction, which are likely overly conservative.

B. Quantitative Trait Analyses

Quantitative endophenotype information is available on a portion of thepostmortem samples that were genotyped. This information includes dataon Braak staging and CERAD plaque estimates. These measures may beanalyzed as a quantitative trait against the SNP genotype data topredict SNPs that associate with specific features of LOAD.

C. Set-Association, ReliefF/MDR and Other Compound Analyses

The analyses described above resulted in the identification of severaltrait-associated SNPs and haplotypes irrespective of potential gene-geneinteractions. A pattern of gene interactions was extracted throughset-association analyses and other compound genetic analyses incollaboration with the investigators noted above. The level ofcomplexity of the existing interactions was very high in this data set.Therefore, only convergent results from both methods were considered forfurther evaluation. Set-association evaluates several sets ofpolymorphic markers throughout the genome and results in a powerfulsingle genome-wide test statistic (See Reference 11). It uses suchrelevant sources of information as allelic association andHardy-Weinberg disequilibrium. This information is combined overmultiple markers and genes in the genome, quality control is improved bytrimming, and permutation tests limit the overall false-positive rate.

Hierarchical cluster analysis was used to allocate significant SNPs andhaplotypes to coherent clusters. Among several proximity values andfusion algorithms the weighted average clustering (fusion algorithm) andthe simple matching coefficient (proximity value) were selected. Thesimple matching coefficient is the most suitable proximity value incases where the values of a binary variable have equal validity. Theweighted average clustering (fusion algorithm) is a balanced clusteringmethod, which can be used for every proximity value and is not prone tostring formation. Neuman et al. provided evidence for the suitability ofcluster analysis in real AD data sets (See Reference 12) and replicatedall chromosomal regions formerly identified by using affected-sib-pairmethods. While the χ2- and logistic regression-based analyses aim atidentifying novel markers and molecular targets, the set-association andhierarchical cluster analyses will establish the optimal combination ofpolymorphic markers for diagnosis and, ultimately, prognosis of AD.

Validation of the SNPs listed in Table 2 may be performed using cohortsthat have been genotyped, using imputation to test the SNPs.Alternatively, a custom array may be designed. Additionally,fine-mapping or sequencing of the regions around the selected SNPs maybe used to identify and/or confirm mutations in coding regions.

TABLE 2 SNPs associated with LOAD SNP Chromosome BP Direct P Valuers429358 19 50103781 4.77E−47 rs4420638 19 50114786 2.05E−45 rs116098519 50095252 9.81E−20 rs7412 19 50103919 3.72E−10 rs17042395 3 165684356.56E−08 rs16889006 5 20995156 2.55E−07 rs5981380 23 74791863 3.55E−07rs11066247 12 111226194 4.57E−07 rs4533297 16 77994546 1.82E−06rs6636980 23 142420716 2.22E−06 rs7895861 10 54057477 2.28E−06 rs663281323 16349702 2.50E−06 rs16834130 1 150731984 3.17E−06 rs264256 1810921528 3.37E−06 rs11217627 11 119379644 4.54E−06 rs13417560 2159733535 5.11E−06 rs13404031 2 159754694 6.34E−06 rs829465 6 724881746.71E−06 rs5955490 23 139369475 6.85E−06 rs1533822 16 26680632 7.12E−06rs2500144 23 142948938 7.69E−06 rs3112160 2 38926825 7.83E−06 rs116768192 105653813 8.91E−06 rs8042680 15 89322341 1.02E−05 rs7908601 1092925026 1.04E−05 rs40666 5 9281171 1.04E−05 rs9351848 6 725017451.09E−05 rs6631389 23 31703010 1.19E−05 rs642612 17 74033121 1.52E−05rs13033552 2 123500876 1.69E−05 rs35306465 4 183306697 1.78E−05rs13395944 2 105655085 1.79E−05 rs1204331 6 72500090 1.89E−05 rs93755556 128589687 2.12E−05 rs2058810 16 48516336 2.25E−05 rs1634508 1731450358 2.36E−05 rs2127470 15 92451058 2.39E−05 rs10079121 5 92816492.50E−05 rs829467 6 72489698 2.63E−05 rs11097396 4 77659357 2.77E−05rs10009946 4 63911889 2.79E−05 rs10783282 12 47433214 2.93E−05 rs67013911 59728371 3.02E−05 rs7064361 23 57978804 3.08E−05 rs16950383 1678006279 3.08E−05 rs6603530 23 118572567 3.10E−05 rs6709683 2 1056777803.13E−05 rs4910821 11 5563215 3.19E−05 rs10400909 15 92450125 3.26E−05rs847386 7 16941578 3.37E−05 rs12186632 5 114049116 3.71E−05 rs125644415 81337307 4.05E−05 rs182174 21 17502225 4.22E−05 rs1256428 15 813188724.32E−05 rs6094509 20 35438689 4.33E−05 rs5987025 23 153663006 4.44E−05rs6865969 5 158435306 4.53E−05 rs4547126 11 5543590 4.62E−05 rs484326716 86357971 4.74E−05 rs10140673 14 94211685 4.78E−05 rs650943 1159763341 5.14E−05 rs1130371 17 31440650 5.15E−05 rs3814127 9 1283055635.15E−05 rs9332441 12 47357512 5.38E−05 rs1954850 11 101883770 5.54E−05rs11038193 11 5561289 5.54E−05 rs10859338 12 91472788 5.55E−05 rs97846315 29361320 5.63E−05 rs6512077 19 15972223 5.85E−05 rs2541286 23146541854 5.85E−05 rs1943229 18 56237438 6.20E−05 rs2286276 7 726252906.27E−05 rs10198042 2 105634020 6.29E−05 rs4286782 6 55431389 6.30E−05rs7535789 1 24480006 6.31E−05 rs2881599 16 26677629 6.37E−05 rs676309 1159758149 6.44E−05 rs6552910 4 186863802 6.53E−05 rs17494056 2 1597609776.70E−05 rs853585 10 119844853 6.85E−05 rs17317101 23 113232500 7.10E−05rs10504376 8 65543485 7.10E−05 rs10742722 11 5542948 7.21E−05 rs225039212 113458972 7.25E−05 rs2881458 15 84959696 7.32E−05 rs16931253 865547912 7.35E−05 rs17025061 2 100943912 7.39E−05 rs9309095 2 430889557.42E−05 rs4113946 12 47310287 7.61E−05 rs2827909 21 23442973 7.64E−05rs9904820 17 43292446 7.89E−05 rs4972391 2 149204738 7.94E−05 rs153091411 59785516 7.97E−05 rs4794346 17 47862514 7.99E−05 rs11133822 515753541 8.20E−05 rs1009987 10 73337354 8.37E−05 rs5962536 23 1046111458.37E−05 rs1359651 20 20706593 8.42E−05 rs10503040 18 56230239 8.45E−05rs4090174 9 131190426 8.50E−05 rs17835266 11 89855586 8.52E−05 rs69832268 1944577 8.65E−05 rs17865911 4 118517807 8.65E−05 rs1582763 11 597785248.67E−05 rs7207413 17 28806787 8.72E−05 rs13013898 2 123512389 8.73E−05rs1202525 1 229018521 8.79E−05 rs2033494 19 22392386 8.82E−05 rs29565815 36538618 9.02E−05 rs40665 5 9281283 9.05E−05 rs9435127 1 91902969.06E−05 rs4648858 1 24479146 9.43E−05 rs4648959 1 24476105 9.44E−05rs1026254 11 59787033 9.63E−05 rs1350089 18 63151304 9.64E−05 rs1040227119 50021054 9.67E−05 rs10742719 11 5542828 9.74E−05 rs2500153 23142964425 9.92E−05 rs6817424 4 81217787 9.95E−05 rs466093 21 301889110.0001012 rs4746100 10 73339711 0.0001021 rs508915 18 41686356 0.0001028rs7108663 11 59784718 0.0001033 rs6591559 11 59782141 0.0001037rs12539316 7 72615834 0.0001039 rs2346709 15 84959609 0.0001057rs10194269 2 105660325 0.0001057 rs5910606 23 118555812 0.0001071rs17835397 11 89857625 0.0001081 rs4357331 8 1925405 0.0001092 rs227736512 47362078 0.0001094 rs17711743 16 77996536 0.0001095 rs11106228 1290561550 0.0001099 rs41407844 4 81219977 0.0001108 rs2136342 13 756177910.0001109 rs3828191 2 165058148 0.000111 rs16951392 17 47845191 0.000112rs1479831 15 92445234 0.000113 rs622920 13 43404671 0.0001142 rs447929717 47818557 0.0001183 rs11095608 23 13162923 0.0001184 rs5978287 238955187 0.0001186 rs9842566 3 16041190 0.0001188 rs953362 20 207015440.0001255 rs4289558 5 15788014 0.0001258 rs10512156 9 86713008 0.0001269rs655231 11 59770433 0.0001279 rs4938931 11 59783189 0.0001281rs12749061 1 62102345 0.0001282 rs12647148 4 60424911 0.0001294rs1442063 18 49377940 0.0001317 rs4342343 5 29350811 0.0001317 rs431536717 72030753 0.000135 rs4794347 17 47862591 0.0001368 rs1019670 1159697175 0.0001383 rs11954932 5 123874867 0.0001384 rs4984259 1561365054 0.0001388 rs2001517 18 54293292 0.0001395 rs6039654 20 99452510.00014 rs1409428 20 20705815 0.0001414 rs17145817 7 72684715 0.0001416rs2278583 2 42843096 0.0001431 rs16931273 8 65555877 0.0001444 rs665487723 8559261 0.0001448 rs2603779 3 16043588 0.0001457 rs7051342 23107420389 0.000146 rs371298 23 118521354 0.0001463 rs12009590 23150635183 0.000147 rs11698059 20 20714260 0.0001474 rs991110 14 608778980.0001478 rs4121392 11 100148633 0.0001481 rs2612600 8 655104600.0001496 rs1102617 21 17521369 0.0001502 rs949973 5 123881433 0.0001519rs11655913 17 30821778 0.0001541 rs3912944 23 86236218 0.0001545rs953363 20 20701683 0.0001566 rs9555552 13 108522077 0.0001573rs3120733 23 154157260 0.0001574 rs6137147 20 20709015 0.0001583rs1277307 4 57591456 0.0001584 rs10077548 5 123876716 0.0001601rs10900908 6 1442522 0.0001604 rs5981711 23 74068338 0.000162 rs67265242 33612197 0.0001637 rs12781952 10 24741698 0.0001647 rs562028 1159634426 0.000165 rs1026255 11 59786525 0.000166 rs17488034 13 263142510.0001674 rs5758223 22 39819866 0.0001674 rs891088 19 7135762 0.0001675rs1945390 11 122025463 0.0001692 rs831480 6 37004806 0.00017 rs846814 9122128253 0.0001715 rs12798784 11 89986271 0.0001718 rs7018850 9 42935170.000172 rs3813097 18 72337990 0.0001724 rs1377334 5 114295122 0.0001725rs10869422 9 70659729 0.0001753 rs16852038 2 215148427 0.0001761rs7161372 14 91866160 0.0001765 rs10426094 19 7156240 0.0001779rs6473080 8 79098294 0.0001785 rs1123024 17 28799974 0.0001791 rs16185136 6477615 0.0001801 rs9434717 1 9190487 0.0001827 rs2827881 21 234278010.0001839 rs6914564 6 135445317 0.000185 rs3208856 19 49988646 0.0001881rs12468287 2 146070764 0.0001902 rs11788891 9 128246019 0.0001911rs4233036 1 24475382 0.0001918 rs1531347 18 48432144 0.0001944rs12336107 9 4300558 0.0001944 rs1805957 5 9287736 0.0001964 rs9374351 6113064907 0.0001984 rs4336923 10 20409004 0.0001993 rs10069190 5123879549 0.0002017 rs4827479 23 65574614 0.000202 rs10897049 1159857157 0.0002043 rs1883487 20 9353485 0.0002065 rs1409427 20 207029590.0002074 rs589605 23 144161283 0.0002088 rs5966049 23 1450277300.0002102 rs4510072 17 28802549 0.0002146 rs4643583 2 56313685 0.0002169rs4744768 9 77610062 0.0002172 rs2232313 23 129457754 0.0002181rs1596039 18 46110711 0.0002184 rs4964586 12 106429621 0.0002188rs6542225 2 115273275 0.000219 rs6705923 2 53037381 0.0002209 rs65515754 61216515 0.0002211 rs1752653 13 26220777 0.0002228 rs957979 1731460821 0.0002232 rs4362707 3 16029235 0.0002278 rs2042922 5 293770580.0002281 rs41323947 1 74617191 0.0002298 rs820255 17 71102117 0.00023rs7298828 12 90558991 0.000231 rs2252238 12 45228174 0.0002311 rs591060723 118555830 0.0002316 rs7824527 8 6877608 0.0002338 rs2398671 5143081401 0.000234 rs1805952 5 9299599 0.0002356 rs1719141 17 314545630.0002383 rs2503285 6 104089558 0.0002384 rs2728524 3 2187318 0.0002386rs10819162 9 128265359 0.0002415 rs1553497 17 28781096 0.0002421rs6683441 1 217024728 0.0002433 rs1879818 8 141516084 0.0002433rs8015610 14 94192101 0.000244 rs7579138 2 42838249 0.0002446 rs171373495 114369300 0.0002447 rs6724143 2 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69914136 0.00101 rs12313149 12 100108354 0.001013 rs1918676 1810751757 0.001013 rs1471994 3 76197670 0.001014 rs1805960 5 92683310.001014 rs1417032 10 7052468 0.001015 rs958935 3 113753102 0.001015rs4862558 4 186829632 0.001016 rs1111218 16 64602993 0.001017 rs61401311 123697134 0.001018 rs3118077 13 50200311 0.001018 rs12084240 123853039 0.001022 rs4743641 9 105107354 0.001024 rs11710973 3 551925520.001025 rs252950 5 160647177 0.001025 rs41381844 5 110683591 0.001025rs4537793 11 117558366 0.00103 rs7220146 17 55081473 0.001031 rs43692161 229264955 0.001033 rs7773435 6 1282034 0.001037 rs853389 6 142987440.001038 rs5956359 23 120693513 0.001039 rs10892873 11 122040543 0.00104rs2181987 14 60887286 0.001041 rs7856017 9 29942326 0.001041 rs802441 786125039 0.001042 rs7197825 16 64590533 0.001043 rs17087898 9 867430310.001044 rs10515029 17 48243948 0.001045 rs9812150 3 134104645 0.001046rs2213369 23 100906897 0.001047 rs7212136 17 22593769 0.00105 rs171921017 31460104 0.001051 rs10773890 12 130421426 0.001053 rs971354 446797872 0.00106 rs1081900 3 120034411 0.001062 rs217034 7 1406524730.001062 rs16995332 20 1500457 0.001063 rs4978968 9 112734176 0.001063rs9999758 4 135959118 0.001066 rs9898218 17 43461633 0.001067 rs96511041 212070341 0.001067 rs2031183 13 112905688 0.001068 rs1966374 415523132 0.001068 rs9504837 6 6473946 0.001068 rs1023964 2 1460763210.001071 rs2398485 12 128843148 0.001072 rs17654608 4 53878489 0.001072rs783376 6 117548067 0.001072 rs11143837 9 76014104 0.001072 rs1084821912 129898081 0.001073 rs2203432 2 98801190 0.001073 rs17133758 1198916596 0.001074 rs10031360 4 126958283 0.001075 rs2900285 9 1320754590.001075 rs2040507 16 71581088 0.001077 rs1939184 11 87266534 0.00108rs12513052 4 181646595 0.001081 rs2057915 7 140653479 0.001081rs12294703 11 27190421 0.001084 rs2447265 15 84954786 0.001084 rs8656716 14735136 0.001084 rs1346440 5 134600906 0.001085 rs16879230 7 337655800.001086 rs4421130 5 36617671 0.001087 rs7606424 2 176986683 0.001088rs17236661 4 77415500 0.00109 rs4829946 23 137800274 0.001092 AFFX- 1159713668 0.001095 SNP_9234256_rs636147 rs11947861 4 189873341 0.001096rs7726558 5 118940497 0.001096 rs890731 5 134602305 0.001098 rs7699718 479098485 0.001099 rs9329143 5 177698849 0.001099 rs12225299 11 598410410.001103 rs4864737 4 53797470 0.001103 rs10110144 8 121074896 0.001103rs8070132 17 55144988 0.001104 rs4961257 8 142301886 0.001105 rs26249386 2474303 0.001106 rs4955753 3 171962804 0.001107 rs4555926 6 1530615940.001107 rs4978970 9 112737852 0.001112 rs7190355 16 64601406 0.001114rs298069 5 59013969 0.001114 rs759112 23 36748565 0.001116 rs321325 645785076 0.001119 rs7086393 10 57920476 0.001122 rs1478281 8 44776850.001123 rs7084673 10 94157067 0.001124 rs8006542 14 88733952 0.001131rs7603548 2 43018651 0.001132 rs4875330 8 4164349 0.001132 rs1002261 986756127 0.001136 rs16864008 2 223266030 0.001138 rs11133248 4 537528590.001138 rs7082405 10 608841 0.001142 rs17599877 5 126216415 0.001142rs2954892 8 114552699 0.001143 rs28515995 23 135648246 0.001145rs4699882 5 65944332 0.001148 rs17056952 9 73341612 0.001148 rs101983172 53807627 0.001149 rs2833325 21 31470453 0.00115 rs3104993 8 966413380.00115 rs1393360 3 79931615 0.001151 rs12829992 12 96604014 0.001155rs7294982 12 44290428 0.001158 rs7517009 1 204082615 0.001163 rs77024915 8050545 0.001163 rs2160491 16 47603070 0.001164 rs6577853 8 1358908450.001164 rs6123167 20 35990953 0.001168 rs4272222 6 53857633 0.001168rs2382492 9 14621836 0.001169 rs7203844 16 47606386 0.00117 rs9390645 6149317560 0.00117 rs1540125 11 78147371 0.001174 rs17602572 11 597049500.001175 rs11266413 23 78430327 0.001177 rs4639843 10 12389096 0.001178rs2544081 12 44301754 0.001178 rs12123186 1 236969721 0.001178 rs29979671 235667890 0.001179 rs641118 1 180054971 0.001181 rs4898337 23101288908 0.001182 rs9780606 23 149072768 0.001182 rs6966132 7 248666860.001182 rs4316805 17 29063736 0.001183 rs9376083 6 135393413 0.001185rs17016207 4 143624532 0.001186 rs35393495 8 13091178 0.001186 rs719636416 7411668 0.001187 rs16857593 2 11593040 0.001187 rs2880301 13 189985349.27E−11 rs7412 19 50103919 3.72E−10 rs12741415 1 200741397 2.49E−09rs1778596 1 143702635 4.46E−09 rs12723357 1 241185135 5.61E−09rs17042395 3 16568435 6.56E−08 rs10199416 2 143462845 7.69E−08 rs42935819 50103781 4.77E−47 rs2898441 21 41528394 0.04743 rs4420638 19 501147862.05E−45

In all SNPs shown in Table 2, the association is in reference to theminor allele in the Caucasian population.

Example 2 Identification of an Allele Associated with Reduced Risk ofLOAD

Numerous SNPs on each chromosome of the human genome have been found tobe associated with LOAD. The rs17042395 SNP on chromosome 3 was found tobe significantly associated with altered Alzheimer's disease (AD) riskin the APOE E3/E3 group. These individuals are homozygous for theneutral form of the APOE risk allele. APOE is the strongest mostreplicated AD risk locus. Thus as determined during development of thepresent invention, when risk at the APOE locus is controlled for, asignificant (surviving genome-wide hypothesis correction) associationwith altered AD risk at this SNP is observed. Remarkably, this SNPsurvives multiple hypothesis correction.

-   P-value (logistic regression): 2.72E-08-   Odds Ratio=0.4045 (for the A-allele)-   Location: Chr. 3, BP 16568435-   SNP ID: rs17042395

The sequence surrounding rs17042395 SNP is set forth as SEQ ID NO:1 withR=A or G:

AAAGAAAGGG GAAAGAAAAG GTATATTTGA AATGGAGACATAGCCCAAGG CTCTTAAACT CAGGGTTATG TCAGTCATGATGTAATAAAA TCATGAGGCC CTACATATAT TGTTTTTCTCCTTTTGGTAT AAGCTTGGGT TTCAGAGCCA TGTTTTTCGACGCCAGTAAA ACTTCCAGCA CTAGCATGGA AATGAACTGCAGTCGATGGC TGCCCTCAAG GTTGGAGAGG GGATAGGAAA CTGGGGCTGC RTTGAACTGGA CAACACTTGT CTGGTCTCAG GTGGATGACTGGTGTCAGCC CAGAATGGCC AGGAGGTGTG GCAAGATTTTCCTGTTTGCC TAAAGAAAGT AACCACTTGG GATCTCCTGCTTGTAAATGT TGGCCCAAGT TTTTGAACTC TACAGGGGCTAAAGAAATCA TCCCCGAGGA CTGAGTTCAG CTTGTGGGTCTCCAGCTTGC GCTCTCTGCT GTTCATTGCT ATAGTCTTGC AAGAAGGTGG. The “A”allele of rs17042395 (SEQ ID NO: 2):GAGAGGGGATAGGAAACTGGGGCTGCATTGAACTGGACAACACTTGTCT GGT. The “G”allele of rs17042395 (SEQ ID NO: 3):GAGAGGGGATAGGAAACTGGGGCTGCGTTGAACTGGACAACACTTGTCT GGT.

Accordingly, this SNP is useful for diagnostic applications innon-carriers of the APOE risk allele (E4 allele). The rs17042395 SNPdoes not lie directly within any known gene in the human genome.Neighboring genes include RFTN1, DAZL, and an uncharacterizedtranscript, BC034913. Thus, these three genes represent novel targetsfor AD, especially for individuals that do not carry the APOE E4 riskallele.

REFERENCES

The references cited herein are expressly incorporated by reference tothe extent allowed, as well as all of the following materials.

-   1. Ritchie K and Kildea D, Lancet 346, 931-94 (1995).-   2. Gatz M et al, J Gerontol A Biol Sci Med Sci 52, M117-M125 (1997).-   3. Ashford J W and Mortimer J A, J Alzheimers Dis 4, 169-177 (2002).-   4. Tanzi R E, and Bertram L. Neuron 32, 181-184 (2001).-   5. Zubenko G S et al, Genomics 50, 121-128 (1998).-   6. Kehoe P et al, Hum Mol Genet 8, 237-245 (1999).-   7. Myers A et al, Am J Med Genet 114, 235-244 (2002).-   8. Risch N and Merikangas K, Science 273, 1516-1517 (1996).-   9. Coon K D et al, J Clin Psychiatry 68, 613-618 (2007).-   10. Reiman E M et al, Neuron. 54, 713-720 (2007).-   11. Hoh J et al, Genome Res 11, 2115-2119 (2001).-   12. Neuman R J et al, Genet Epidemiol 19, S57-63 (2000).

1. A method of classifying a subject to a late onset Alzheimer's disease(LOAD) risk group, comprising: receiving a sample from the subject;detecting a marker in Table 2; and classifying the subject into a riskgroup based upon the presence or absence of the marker.
 2. The method ofclaim 1, further comprising isolating nucleic acid from the sample. 3.The method of claim 1, wherein the marker is detected directly.
 4. Themethod of claim 3, wherein detecting the marker further comprises amethod selected from the group consisting of Sanger sequencing,pyrosequencing, SOLID sequencing, massively parallel sequencing,barcoded DNA sequencing, PCR, real-time PCR, quantitative PCR,microarray analysis of genomic DNA with a gene chip, restrictionfragment length polymorphism analysis, allele specific ligation, andcomparative genomic hybridization.
 5. The method of claim 1, wherein themarker is detected indirectly.
 6. The method of claim 5, whereindetecting the marker further comprises a method selected from the groupconsisting of microarray analysis of RNA, RNA in situ hybridization,RNAse protection assay, Northern blot, reverse transcriptase PCR,quantitative PCR, quantitative reverse transcriptase PCR, quantitativereal-time reverse transcriptase PCR, reverse transcriptase treatmentfollowed by direct sequencing, flow cytometry, immunohistochemistry,ELISA, Western blot, immunoaffinity chromatograpy, HPLC, massspectrometry, protein microarray analysis, PAGE analysis, isoelectricfocusing, and 2-D gel electrophoresis.
 7. The method of claim 1, whereinthe marker is associated with a high risk of developing LOAD and thesubject is classified to a risk group with high risk of LOAD if themarker is detected in the sample.
 8. The method of claim 7, wherein thesubject is further classified based on the presence or absence of theAPOE-ε4 allele.
 9. The method of claim 1, wherein the marker isassociated with a low risk of developing LOAD and the subject isclassified to a risk group with low risk of LOAD if the marker isdetected in the sample.
 10. The method of claim 9, wherein the marker isthe A allele of rs17042395.
 11. The method of claim 10, wherein thesubject is further classified based on the presence of two copies of theAPOE-e3 allele.
 12. A set of molecular probes used in assessing the riskof developing late onset Alzheimer's disease (LOAD) comprising: a firstprobe capable of detecting a first SNP selected from Table 2; and asecond probe capable of detecting a second SNP selected from Table 2;wherein the probes are associated with a microarray of 1000 or fewerelements.
 13. The set of claim 12, wherein the first probe is capable ofdetecting a SNP associated with a higher risk of developing LOAD. 14.The set of claim 13, wherein the second probe is capable of detecting aSNP associated with a lower risk of developing LOAD.
 15. The set ofclaim 12, wherein the first probe and the second probe are capable ofdetecting a SNP associated with a lower risk of developing LOAD.
 16. Theset of claim 15, wherein the first probe detects the A allele ofrs17042395 and the second probe detects the apoe3 allele.
 17. A methodof classifying a subject to a late onset Alzheimer's disease (LOAD) riskgroup, comprising: receiving a sample from the subject; detecting an Aallele of rs17042395; detecting an E3 allele of APOE; and classifyingthe subject in a low LOAD risk group if both the A allele of rs17042395and the E3 allele of APOE are detected.
 18. The method of claim 17,further comprising isolating nucleic acid from the sample.
 19. Themethod of claim 17, wherein the marker is detected directly.
 20. Themethod of claim 19, wherein detecting the marker further comprises amethod selected from the group consisting of Sanger sequencing,pyrosequencing, SOLID sequencing, massively parallel sequencing,barcoded DNA sequencing, PCR, real-time PCR, quantitative PCR,microarray analysis of genomic DNA with a gene chip, restrictionfragment length polymorphism analysis, allele specific ligation, andcomparative genomic hybridization.
 21. The method of claim 17, whereinthe marker is detected indirectly.
 22. The method of claim 21, whereindetecting the marker further comprises a method selected from the groupconsisting of microarray analysis of RNA, RNA in situ hybridization,RNAse protection assay, Northern blot, reverse transcriptase PCR,quantitative PCR, quantitative reverse transcriptase PCR, quantitativereal-time reverse transcriptase PCR, reverse transcriptase treatmentfollowed by direct sequencing, flow cytometry, immunohistochemistry,ELISA, Western blot, immunoaffinity chromatograpy, HPLC, massspectrometry, protein microarray analysis, PAGE analysis, isoelectricfocusing, and 2-D gel electrophoresis.